TY - GEN
T1 - Aerial Interaction with Tactile Sensing
AU - Guo, Xiaofeng
AU - He, Guanqi
AU - Mousaei, Mohammadreza
AU - Geng, Junyi
AU - Shi, Guanya
AU - Scherer, Sebastian
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - While the field of autonomous Uncrewed Aerial Vehicles (UAVs) has grown rapidly, most applications only focus on passive visual tasks. Aerial interaction aims to execute tasks involving physical interactions, which offers a way to assist humans in high-altitude and high-risk operations. Tactile sensors, being both cost-effective and lightweight, are capable of sensing contact information including force distribution, as well as recognizing local textures. In this paper, we pioneer the use of vision-based tactile sensors on fully actuated UAVs in dynamic aerial manipulation tasks. We introduce a pipeline utilizing tactile feedback for force tracking via a hybrid motion-force controller and a method for wall texture detection during aerial interactions. Our experiments demonstrate that our system can effectively replace or complement traditional force/torque (F/T) sensors. Compared with only using the F/T sensor, our approach offers two solutions: substitution with tactile sensing, achieving comparable flight performance, or integration of tactile sensing with F/T sensor feedback, leading to around 16% improvement in position tracking accuracy. Our algorithm achieves 93.4% accuracy in real-time texture recognition, which further escalates to 100% in post-contact analysis. To the best of our knowledge, this is the first work to incorporate a vision-based tactile sensor into aerial interaction tasks.
AB - While the field of autonomous Uncrewed Aerial Vehicles (UAVs) has grown rapidly, most applications only focus on passive visual tasks. Aerial interaction aims to execute tasks involving physical interactions, which offers a way to assist humans in high-altitude and high-risk operations. Tactile sensors, being both cost-effective and lightweight, are capable of sensing contact information including force distribution, as well as recognizing local textures. In this paper, we pioneer the use of vision-based tactile sensors on fully actuated UAVs in dynamic aerial manipulation tasks. We introduce a pipeline utilizing tactile feedback for force tracking via a hybrid motion-force controller and a method for wall texture detection during aerial interactions. Our experiments demonstrate that our system can effectively replace or complement traditional force/torque (F/T) sensors. Compared with only using the F/T sensor, our approach offers two solutions: substitution with tactile sensing, achieving comparable flight performance, or integration of tactile sensing with F/T sensor feedback, leading to around 16% improvement in position tracking accuracy. Our algorithm achieves 93.4% accuracy in real-time texture recognition, which further escalates to 100% in post-contact analysis. To the best of our knowledge, this is the first work to incorporate a vision-based tactile sensor into aerial interaction tasks.
UR - http://www.scopus.com/inward/record.url?scp=85202433377&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85202433377&partnerID=8YFLogxK
U2 - 10.1109/ICRA57147.2024.10611282
DO - 10.1109/ICRA57147.2024.10611282
M3 - Conference contribution
AN - SCOPUS:85202433377
T3 - Proceedings - IEEE International Conference on Robotics and Automation
SP - 1576
EP - 1582
BT - 2024 IEEE International Conference on Robotics and Automation, ICRA 2024
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2024 IEEE International Conference on Robotics and Automation, ICRA 2024
Y2 - 13 May 2024 through 17 May 2024
ER -